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Modeling Product Form Preference Using Gestalt Principles, Semantic Space, and Kansei

[+] Author Affiliations
José E. Lugo, Stephen M. Batill, Laura Carlson

University of Notre Dame, Notre Dame, IN

Paper No. DETC2012-70434, pp. 529-539; 11 pages
doi:10.1115/DETC2012-70434
From:
  • ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 7: 9th International Conference on Design Education; 24th International Conference on Design Theory and Methodology
  • Chicago, Illinois, USA, August 12–15, 2012
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4506-6
  • Copyright © 2012 by ASME

abstract

Engineers describe design concepts using design variables. Users develop their visual judgment of products by mentally grouping design variables according to Gestalt principles, extracting meaning using semantic dimensions and attaching attributes to the products, as reflected in Kansei methodology. The goal of this study was to assess how these different sources of information and representations of product form (design variables, Gestalt variables, Kansei attributes, and semantic dimensions) could combine to best predict product preference for both designers and users. Sixteen wheel rim designs were created using four design variables that were also combined into higher-order Gestalt variables. Sixty-four participants viewed each rim, and rated it according to semantic dimensions and Kansei attributes, and provided an overall “like” rating. The most reliable prediction of product preference were developed using Gestalt variables in combination with the meaning and emotion the users attached to the product. Finally, implications for designers are discussed.

Copyright © 2012 by ASME
Topics: Modeling , Preferences

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